Title :
Fuzzy model optimization based on cooperative evolutionary genetic algorithm
Author_Institution :
Sch. of Inf., Linyi Univ., Linyi, China
Abstract :
Interpretability and accuracy are base requirements of fuzzy model. An approach to construct fuzzy model based on co-evolutionary genetic algorithm is proposed for the requirements. First, the initial fuzzy system is identified using WM method because of its simplicity and quickness to generate fuzzy rules. The membership functions and fuzzy rule base are optimized by the co-evolutionary genetic algorithm in order to improve accuracy of the fuzzy model. The result of simulation experiment shows its validity.
Keywords :
fuzzy set theory; fuzzy systems; genetic algorithms; WM method; coevolutionary genetic algorithm; cooperative evolutionary genetic algorithm; fuzzy model optimization; fuzzy rule base; fuzzy rules generation; initial fuzzy system; interpretability; membership functions; Encoding; co-evolutionary; fuzzy control; fuzzy model; genetic algorithm; simulation Introduction;
Conference_Titel :
Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2363-5
DOI :
10.1109/EEESym.2012.6258729
